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Calibrating environmental DNA metabarcoding to conventional surveys for measuring fish species richness

August 28, 2020

The ability to properly identify species present in a landscape is foundational to ecology and essential for natural resource management and conservation. However, many species are often unaccounted for due to ineffective direct capture and visual surveys, especially in aquatic environments. Environmental DNA metabarcoding is an approach that overcomes low detection probabilities and should consequently enhance estimates of biodiversity and its proxy, species richness. Here, we synthesize 37 studies in natural aquatic systems to compare species richness estimates for bony fish between eDNA metabarcoding and conventional methods, such as nets, visual census, and electrofishing. In freshwater systems with fewer than 100 species, we found eDNA metabarcoding detected more species than conventional methods. Using multiple genetic markers further increased species richness estimates with eDNA metabarcoding. For more diverse freshwater systems and across marine systems, eDNA metabarcoding reported similar values of species richness to conventional methods; however, more studies are needed in these environments to better evaluate relative performance. In systems with greater biodiversity, eDNA metabarcoding will require more populated reference databases, increased sampling effort, and multi-marker assays to ensure robust species richness estimates to further validate the approach. eDNA metabarcoding is reliable and provides a path for broader biodiversity assessments that can outperform conventional methods for estimating species richness.

Citation Information

Publication Year 2020
Title Calibrating environmental DNA metabarcoding to conventional surveys for measuring fish species richness
DOI 10.3389/fevo.2020.00276
Authors Mary E McElroy, Terra L Dressler, Georgia C Titcomb, Emily A Wilson, Kristy Deiner, Tom L. Dudley, Erika J. Eliason, Nathan T Evans, Steven D Gaines, Kevin D. Lafferty, Gary A Lamberti, Yiyuan Li, David M. Lodge, Milton S. Love, Andrew R. Mahon, Michael E Pfrender, Mark A Renshaw, Kimberly A Selkoe, Christopher L. Jerde
Publication Type Article
Publication Subtype Journal Article
Series Title Frontiers in Ecology and Evolution
Index ID 70220558
Record Source USGS Publications Warehouse
USGS Organization Western Ecological Research Center